Description

n8n-nodes-astradb

A comprehensive community node for n8n that provides seamless integration with DataStax Astra DB, a serverless NoSQL database with advanced vector capabilities for AI/ML applications.

🚀 Features

• Full CRUD Operations: Complete document lifecycle management
• Vector Search: Advanced AI/ML vector similarity search capabilities
• Batch Operations: Efficient bulk operations for large datasets
• Atomic Operations: ACID-compliant find and update/replace/delete operations
• Advanced Querying: Support for complex filters, projections, and sorting
• Connection Testing: Built-in credential validation and connection testing
• Error Handling: Comprehensive error handling with retry mechanisms
• Type Safety: Full TypeScript support with comprehensive type definitions
• Performance Optimized: Connection pooling and query optimization

📦 Installation

Method 1: npm (Recommended)

npm install n8n-nodes-astradb

Method 2: Community Nodes Installation

1. In your n8n instance, go to Settings → Community Nodes
2. Click Install a community node
3. Enter n8n-nodes-astradb
4. Click Install

Method 3: Manual Installation

1. Download the latest release from GitHub
2. Extract to your n8n community nodes directory
3. Run npm install in the extracted directory

⚙️ Configuration

Credentials Setup

Create an Astra DB API credential with the following fields:

• Endpoint: Your Astra DB endpoint URL
  • Format: https://your-database-id-your-region.apps.astra.datastax.com
  • Example: https://abc123-def456-us-east1.apps.astra.datastax.com
• Token: Your Astra DB application token

Getting Your Credentials

1. Create Astra DB Database:

   • Go to DataStax Astra
   • Sign up or log in to your account
   • Create a new database or select an existing one

2. Get Connection Details:

   • Navigate to your database dashboard
   • Go to the Connect tab
   • Copy your Endpoint URL
   • Generate an Application Token (with appropriate permissions)

3. Configure in n8n:

   • In n8n, go to Credentials → Add Credential
   • Search for "Astra DB API"
   • Enter your endpoint and token
   • Test the connection

🔧 Operations

📝 Insert Operations

Insert One

Insert a single document into a collection.

Parameters:

• Keyspace: The keyspace name
• Collection: The collection name
• Document: JSON document to insert

Example:

{
  "name": "Ni2 Maddy",
  "email": "ni2maddy@bits.com",
  "age": 30,
  "createdAt": "2024-01-01T00:00:00Z"
}

Insert Many

Insert multiple documents in a single operation.

Parameters:

• Keyspace: The keyspace name
• Collection: The collection name
• Documents: Array of JSON documents
• Options: Additional options (limit, skip, etc.)

Example:

[
  {
    "name": "John Doe",
    "email": "john@example.com"
  },
  {
    "name": "Jane Smith", 
    "email": "jane@example.com"
  }
]

🔍 Find Operations

Find Many

Find multiple documents matching filter criteria.

Parameters:

• Keyspace: The keyspace name
• Collection: The collection name
• Filter: JSON filter criteria
• Options: Query options (limit, skip, sort, projection)

Find One

Find a single document matching filter criteria.

Parameters:

• Keyspace: The keyspace name
• Collection: The collection name
• Filter: JSON filter criteria
• Options: Query options

✏️ Update Operations

Update Many

Update multiple documents matching filter criteria.

Parameters:

• Keyspace: The keyspace name
• Collection: The collection name
• Filter: JSON filter criteria
• Update: JSON update operations
• Options: Update options (upsert, etc.)

Update Example:

{
  "$set": {
    "lastLogin": "2024-01-01T12:00:00Z",
    "status": "active"
  },
  "$inc": {
    "loginCount": 1
  }
}

Find and Update

Atomically find and update a single document.

Parameters:

• Keyspace: The keyspace name
• Collection: The collection name
• Filter: JSON filter criteria
• Update: JSON update operations
• Options: Update options (upsert, returnDocument)

Find and Replace

Atomically find and replace a single document.

Parameters:

• Keyspace: The keyspace name
• Collection: The collection name
• Filter: JSON filter criteria
• Replacement: Complete replacement document
• Options: Update options

🗑️ Delete Operations

Delete

Delete documents matching filter criteria.

Parameters:

• Keyspace: The keyspace name
• Collection: The collection name
• Filter: JSON filter criteria

Find and Delete

Atomically find and delete a single document.

Parameters:

• Keyspace: The keyspace name
• Collection: The collection name
• Filter: JSON filter criteria
• Options: Query options

📊 Utility Operations

Estimated Document Count

Get an estimated count of documents in the collection.

Parameters:

• Keyspace: The keyspace name
• Collection: The collection name
• Options: Query options

🔍 Query Examples

Basic Filters

// Exact match
{
  "name": "John Doe"
}

// Range queries
{
  "age": { "$gte": 18, "$lt": 65 }
}

// Array operations
{
  "tags": { "$in": ["premium", "vip"] }
}

Complex Filters

{
  "$and": [
    { "status": "active" },
    { "$or": [
      { "role": "admin" },
      { "role": "user" }
    ]},
    { "createdAt": { "$gte": "2024-01-01T00:00:00Z" } }
  ]
}

Sort Options

{
  "name": 1,        // Ascending
  "createdAt": -1   // Descending
}

Projection

{
  "name": 1,        // Include
  "email": 1,       // Include
  "_id": 0          // Exclude
}

🤖 Vector Operations

Astra DB provides powerful vector search capabilities for AI/ML applications:

Insert Vector Document

{
  "text": "Sample document content",
  "embedding": [0.1, 0.2, 0.3, 0.4, 0.5],
  "metadata": {
    "source": "document.pdf",
    "page": 1,
    "category": "technical"
  }
}

Vector Search

{
  "embedding": [0.1, 0.2, 0.3, 0.4, 0.5],
  "similarity": 0.8,
  "vectorFilter": {
    "category": "technical"
  }
}

Vector Search Options

• Embedding: Vector array for similarity search
• Similarity Threshold: Minimum similarity score (0-1)
• Vector Filter: Additional filter criteria
• Limit: Maximum number of results

⚡ Advanced Options

Query Options

• Limit: Maximum documents to return (1-1000)
• Skip: Number of documents to skip (pagination)
• Sort: Sort criteria with field and direction
• Projection: Fields to include/exclude
• Upsert: Create document if not found (update operations)
• Return Document: Return before/after version (atomic operations)

Additional Options

• Continue on Fail: Continue processing other items on failure
• Timeout: Operation timeout in seconds (1-300)
• Retry Attempts: Number of retry attempts (0-10)

🛡️ Error Handling

The node includes comprehensive error handling:

• Connection Errors: Automatic retry with exponential backoff
• Validation Errors: Clear error messages for invalid inputs
• Query Errors: Detailed error information for failed operations
• Continue on Fail: Option to continue processing other items on individual failures
• Input Sanitization: Protection against injection attacks
• Type Safety: Runtime type checking and validation

🧪 Testing

Unit Tests

npm test

Test Coverage

npm run test:coverage

Watch Mode

npm run test:watch

🚀 Development

Prerequisites

• Node.js 18.17.0 or higher
• npm or yarn
• Astra DB account and database

Setup

git clone https://github.com/msmygit/n8n-nodes-astradb.git
cd n8n-nodes-astradb
npm install

Build

npm run build

Development Mode

npm run dev

Linting

npm run lint
npm run lint:fix

📚 Examples

Basic CRUD Workflow

1. Trigger: Schedule or webhook
2. Astra DB – Find: Query existing data
3. Astra DB – Update: Modify documents
4. Astra DB – Insert: Add new documents

Vector Search Workflow

1. Trigger: Document upload
2. AI Embedding: Generate vector embeddings
3. Astra DB – Insert: Store document with embeddings
4. Astra DB – Vector Search: Find similar documents

Data Migration Workflow

1. Trigger: Manual or scheduled
2. Astra DB – Find Many: Query source data
3. Transform: Process and clean data
4. Astra DB – Insert Many: Bulk insert to target

🤝 Contributing

We welcome contributions! Please follow these steps:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Development Guidelines

• Follow TypeScript best practices
• Add tests for new functionality
• Update documentation
• Follow the existing code style
• Ensure all tests pass

📄 License

This project is licensed under the MIT License – see the LICENSE file for details.

🆘 Support

Documentation

• Astra DB Documentation
• n8n Community Nodes Guide

Community Support

• GitHub Issues
• n8n Community Forum
• DataStax Community

Professional Support

• DataStax Support
• n8n Enterprise Support

🏆 Acknowledgments

• DataStax for providing Astra DB, an excellent knowledge layer
• n8n team for the platform
• Community contributors and testers

📈 Roadmap

Version 1.1 (Planned)

• Advanced aggregation operations
• Real-time change streams
• Enhanced vector search features
• Performance monitoring

Version 1.2 (Planned)

• Multi-region support
• Advanced security features
• Custom authentication methods
• Enhanced error reporting

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Made with ❤️ for the n8n and IBM DataStax communities